It is widely acknowledged that traditional Project Management techniques are no longer sufficient, as projects become more complex and client's demand reduced timescales. Problems that arise include inadequate planning and risk analysis, ineffective project monitoring and control, and uninformed post-mortem analysis. Effective modelling techniques, which capture the complexities of such projects, are therefore necessary for adequate project management. This book looks at those issues, describes some modelling techniques, then discusses their merits and possible synthesis.
- This is the only project management book that deals with Project Modelling.
- Features case studies throughout.
- Places the various approaches to Project Modelling within a coherent framework, and gives an objective overview.
Table of Contents:
1 This Book 1
Introduction to the book and the author 1
Why is there a need for this book? 3
The structure of this book 7
What do I need to know before I read this book? 8
Conclusion 11
2 Projects 13
What is a project? 13
What are project objectives? 15
Basic project management techniques 18
Projects referred to in this book 23
Conclusion 29
3 Modelling 31
What is a model? 31
Why do we model? 35
Modelling in practice 40
Validation 44
Conclusion 47
4 What is a Complex Project? 49
Introduction 49
What is complexity? Structural complexity 50
What is complexity? Uncertainty 55
What is complexity? Summary 58
Increasing complexity 59
Tools and techniques—and the way ahead 62
5 Discrete Effects and Uncertainty 65
Introduction 65
Uncertainty and risk in projects 66
Cost risk: additive calculations 78
Time risk: effects in a network 89
Analysing time risk: simulation 96
Criticality and cruciality 104
The three criteria and beyond 115
Conclusion 118
6 Discrete Effects: Collecting Data 119
Introduction 119
Collecting subjective data: identification 121
Collecting subjective data: general principles of quantification 123
Collecting subjective data: simple activity-duration models 126
Effect of targets 131
Conclusion 136
7 The Soft Effects 137
Introduction 137
Some key project characteristics 139
Client behaviour and external effects on the project 140
Management decisions 146
Project staffing 149
Subjective effects within the project 151
Summary and looking forward 154
8 Systemic Effects 155
The effects 155
A brief introduction to cause mapping 157
Qualitative modelling: simple compounding 158
Qualitative modelling: loops 161
Quantitative modelling 163
9 System Dynamics Modelling 167
Introduction to system dynamics 167
Using system dynamics with mapping 171
Elements of models 175
Production elements 176
Other elements 188
Managerial actions 189
How effects compound 193
Validation 195
Conclusion 196
10 Hybrid Methods: The Way Forward? 199
Introduction 199
Adapting standard models using lessons learned from SD 200
Using conventional tools to generate SD models 205
Using SD and conventional models to inform each other 206
Extending SD: discrete events and stochastic SD 208
The need for intelligence 210
Conclusion 212
11 The Role of the Modeller 215
Introduction 215
Project management 215
What makes a good modeller? 217
Stages of project modelling 219
Chapter summary 230
12 Conclusion 233
Appendix: Extension of time claims 235
References 249
Index 265
